Algorithms Lesson 4: Quicksort
Why Stack Overflow recommends it
Stack Overflow users link it when asking about or debugging quicksort implementations, as a quick visual explanation of how pivoting and partitioning work.
Recommended by 1 people across 1 different months, 2014 to 2015.
What it is
A 4.5-minute lesson from XoaX.net that explains the quicksort algorithm with graphical step-by-step demonstrations and a pseudocode implementation. It is part of a short algorithms course of narrated lessons.
What people said
Recommends Revive · 2014-06 · Stack Overflow · on “Quick Sort Algorithm showing Wrong Output”
@user3728933 I dont think you fully understand the quick sort algorithm. Your code doesnt look like its choosing a pivot to sort around at all/correctly. Here is a good link which explains how quick sort works [this video]
Cites Yoda · 2015-03 · Stack Overflow · on “Stackoverflow exception caused by recursive call of partitionStep in QuickSort”
I try to implement quicksort algorithm for int[] . I coded the partition step correctly but then I wanted to call partition step method recursively to get the array sorted, unfortunately I pass wrong indexes to the recursive call and I get StackOverflow exception. I based it on: [this video] public class Quicksort { public static void partition(int[] t, int i, int j) { int start = i, end = j; int pivot = t[(i + j) / 2]; // select the pivot as the middle value System.out.println("pivot: " + pivot); int temp; while (i < j) { while (t[i] < pivot) { // looking for value greater or equal to the // pivot i++; } while (t[j] > pivot) { // looking for value lower or equal to the // pivot j--; } System.out
Cites kungfuspider · 2015-06 · Stack Overflow · on “Quicksort efficiency: does direction of scan matter?”
Here is my implementation of an in-place quicksort algorithm, an adaptation from this [this video] video: def partition(arr, start, size): if (size < 2): return index = int(math.floor(random.random()*size)) L = start U = start+size-1 pivot = arr[start+index] while (L < U): while arr[L] < pivot: L = L + 1 while arr[U] > pivot: U = U - 1 temp = arr[L] arr[L] = arr[U] arr[U] = temp partition(arr, start, L-start) partition(arr, L+1, size-(L-start)-1) There seems to be a few implementations of the scanning step where the array (or current portion of the array) is divided into 3 segments: elements lower than the pivot, the pivot, and elements greater than the pivot. I am scanning from the left for elem